README.md

metadata

title: Medical RAG with Meditron-7B-LLM
emoji: 📚
colorFrom: blue
colorTo: indigo
sdk: docker
sdk_version: 20.10.17
app_file: app.py
pinned: false
license: apache-2.0
short_description: A specialized AI assistant for medical information retrieval

Medical RAG QA System

A Retrieval-Augmented Generation (RAG) system for medical question answering using:

• Meditron-7B LLM
• Qdrant Vector Database
• PubMedBERT Embeddings

Features

• PDF document ingestion
• Semantic search with medical embeddings
• LLM-powered question answering
• Source document citation

🚀 Usage

1. Query Interface:

import requests

response = requests.post("https://d221/Qdrant_Backend.hf.space/get_response", 
                         data={"query": "What are the symptoms of diabetes?"})
print(response.json())